Software Engineer - AI Data Pipelines (Remote)

Speechify; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Speechify, a fully distributed company with no office, is seeking a Software Engineer - AI Data to build the data pipelines that power our model training and next‑generation AI products. You will help assemble high‑quality datasets at petabyte scale by blending engineering, infrastructure, and research.

You’ll discover new data sources, design and optimize large‑scale data‑processing systems for quality and cost, and collaborate closely with AI scientists to improve training datasets and models.

Qualifications

• Degree in Computer Science or a related field or equivalent practical experience.
• 5+ years of professional software engineering experience.
• Proficiency in Python and Bash in Linux environments.
• Experience building and operating production systems, ideally involving data pipelines or large-scale data processing.
• Strong problem-solving skills, initiative, and the ability to work independently in ambiguous environments.

Responsibilities

• Discover new sources of audio data and build reliable pipelines to bring them into our training datasets.
• Build and improve large-scale data-processing systems, optimizing for data quality, throughput, and cost.
• Collaborate closely with AI Scientists to improve training datasets and support the development of next-generation models.
• Take ownership of engineering projects from problem discovery through implementation and continuous improvement.

Skills

Backend development

Python

Bash

Data pipelines

Problem solving

Independent work

Education

Computer Science degree

Tools

Linux

GCP

Terraform

Job description

Speechify, a fully distributed company with no office, is seeking a Software Engineer - AI Data to build the data pipelines that power our model training and next‑generation AI products. You will help assemble high‑quality datasets at petabyte scale by blending engineering, infrastructure, and research.

You’ll discover new data sources, design and optimize large‑scale data‑processing systems for quality and cost, and collaborate closely with AI scientists to improve training datasets and models.